importance
#> [[1]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[2]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[3]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[4]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[5]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[6]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[7]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[8]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[9]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[10]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[11]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[12]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[13]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[14]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[15]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[16]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[17]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[18]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[19]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[20]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[21]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[22]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[23]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[24]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[25]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[26]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[27]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[28]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[29]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[30]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[31]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[32]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[33]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[34]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[35]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[36]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[37]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[38]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[39]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[40]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[41]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[42]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[43]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[44]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[45]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[46]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[47]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[48]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[49]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[50]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[51]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[52]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[53]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[54]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[55]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[56]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[57]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[58]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[59]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[60]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[61]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[62]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[63]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[64]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[65]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[66]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[67]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[68]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[69]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[70]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[71]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[72]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[73]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[74]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[75]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[76]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[77]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[78]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[79]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[80]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[81]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[82]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[83]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[84]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[85]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[86]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[87]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[88]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[89]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[90]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[91]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[92]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[93]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[94]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[95]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[96]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[97]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[98]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[99]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[100]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[101]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[102]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[103]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[104]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[105]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[106]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[107]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[108]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[109]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[110]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[111]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[112]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[113]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[114]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[115]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[116]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[117]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[118]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[119]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[120]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[121]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[122]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[123]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[124]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[125]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[126]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[127]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[128]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[129]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[130]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[131]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[132]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[133]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[134]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[135]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[136]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[137]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[138]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[139]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[140]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[141]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[142]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[143]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[144]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[145]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[146]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[147]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[148]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[149]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[150]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[151]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[152]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[153]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[154]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[155]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[156]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[157]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[158]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[159]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[160]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[161]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[162]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[163]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[164]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[165]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[166]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[167]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[168]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[169]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[170]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[171]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[172]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[173]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[174]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[175]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[176]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[177]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[178]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[179]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[180]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[181]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[182]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[183]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[184]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[185]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[186]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[187]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[188]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[189]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[190]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[191]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[192]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[193]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[194]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[195]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[196]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[197]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[198]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[199]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[200]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[201]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[202]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[203]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[204]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[205]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[206]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[207]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[208]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[209]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[210]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[211]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[212]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[213]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[214]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[215]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[216]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[217]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[218]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[219]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[220]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[221]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[222]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[223]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[224]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[225]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[226]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[227]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[228]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[229]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[230]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[231]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[232]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[233]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[234]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[235]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[236]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[237]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[238]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[239]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[240]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[241]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[242]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[243]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[244]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[245]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[246]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[247]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[248]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[249]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[250]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[251]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[252]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[253]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[254]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[255]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[256]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[257]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[258]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[259]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[260]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[261]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[262]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[263]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[264]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[265]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[266]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[267]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[268]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[269]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[270]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[271]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[272]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[273]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[274]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[275]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[276]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[277]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[278]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[279]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[280]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[281]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[282]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[283]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[284]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[285]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[286]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[287]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[288]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[289]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[290]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[291]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[292]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[293]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[294]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[295]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[296]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[297]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[298]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[299]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[300]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[301]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[302]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[303]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[304]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[305]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[306]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[307]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[308]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[309]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[310]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[311]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[312]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[313]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[314]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[315]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[316]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[317]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[318]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[319]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[320]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[321]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[322]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[323]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[324]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[325]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[326]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[327]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[328]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[329]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[330]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[331]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[332]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[333]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[334]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[335]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[336]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[337]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[338]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[339]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[340]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[341]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[342]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[343]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[344]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[345]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[346]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[347]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[348]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[349]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[350]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[351]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[352]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[353]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[354]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[355]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[356]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[357]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[358]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[359]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[360]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[361]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[362]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[363]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[364]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[365]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[366]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[367]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[368]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[369]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[370]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[371]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[372]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[373]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[374]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[375]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[376]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[377]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[378]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[379]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[380]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[381]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[382]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[383]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[384]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[385]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[386]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[387]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[388]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[389]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[390]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[391]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[392]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[393]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[394]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[395]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[396]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[397]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[398]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[399]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[400]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[401]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[402]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[403]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[404]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[405]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[406]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[407]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[408]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[409]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[410]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[411]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[412]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[413]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[414]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[415]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[416]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[417]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[418]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[419]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[420]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[421]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[422]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[423]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[424]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[425]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[426]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[427]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[428]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[429]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[430]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[431]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[432]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[433]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[434]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[435]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[436]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[437]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[438]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[439]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[440]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[441]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[442]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[443]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[444]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[445]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[446]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[447]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[448]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[449]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[450]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[451]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[452]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[453]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[454]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[455]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[456]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[457]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[458]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[459]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[460]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[461]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[462]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[463]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[464]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[465]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[466]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[467]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[468]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[469]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[470]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[471]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[472]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[473]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[474]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[475]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[476]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[477]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[478]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[479]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[480]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[481]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[482]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[483]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[484]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[485]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[486]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[487]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[488]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[489]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[490]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[491]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[492]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[493]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[494]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[495]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[496]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[497]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[498]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[499]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[500]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[501]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[502]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[503]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[504]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[505]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[506]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[507]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[508]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[509]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[510]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[511]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[512]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[513]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[514]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[515]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[516]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[517]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[518]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[519]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[520]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[521]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[522]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[523]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[524]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[525]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[526]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[527]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[528]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[529]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[530]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[531]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[532]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[533]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[534]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[535]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[536]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[537]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[538]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[539]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[540]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[541]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[542]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[543]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[544]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[545]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[546]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[547]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[548]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[549]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[550]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[551]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[552]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[553]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[554]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[555]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[556]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[557]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[558]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[559]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[560]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[561]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[562]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[563]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[564]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[565]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[566]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[567]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[568]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[569]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[570]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[571]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[572]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[573]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[574]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[575]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[576]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[577]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[578]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[579]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[580]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[581]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[582]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[583]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[584]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[585]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[586]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[587]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[588]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[589]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[590]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[591]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[592]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[593]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[594]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[595]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[596]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[597]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[598]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[599]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[600]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[601]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[602]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[603]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[604]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[605]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[606]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[607]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[608]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[609]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[610]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[611]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[612]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[613]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[614]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[615]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[616]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[617]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[618]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[619]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[620]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[621]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[622]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[623]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[624]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[625]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[626]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[627]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[628]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[629]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[630]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[631]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[632]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[633]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[634]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[635]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[636]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[637]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[638]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[639]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[640]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[641]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[642]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[643]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[644]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[645]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[646]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[647]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[648]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[649]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[650]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[651]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[652]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[653]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[654]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[655]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[656]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[657]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[658]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[659]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[660]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[661]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[662]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[663]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[664]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[665]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[666]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[667]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[668]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[669]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[670]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[671]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[672]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[673]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[674]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[675]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[676]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[677]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[678]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[679]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[680]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[681]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[682]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[683]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[684]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[685]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[686]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[687]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[688]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[689]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[690]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[691]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[692]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[693]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[694]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[695]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[696]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[697]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[698]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[699]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[700]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[701]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[702]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[703]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[704]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[705]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[706]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[707]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[708]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[709]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[710]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[711]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[712]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[713]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[714]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[715]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[716]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[717]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[718]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[719]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[720]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[721]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[722]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[723]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[724]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[725]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[726]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[727]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[728]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[729]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[730]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[731]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[732]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[733]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[734]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[735]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[736]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[737]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[738]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[739]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[740]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[741]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[742]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[743]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[744]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[745]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[746]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[747]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[748]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[749]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[750]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[751]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[752]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[753]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[754]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[755]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[756]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[757]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[758]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[759]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[760]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[761]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[762]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[763]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[764]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[765]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[766]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[767]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[768]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[769]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[770]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[771]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[772]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[773]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[774]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[775]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[776]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[777]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[778]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[779]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[780]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[781]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[782]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[783]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[784]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[785]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[786]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[787]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[788]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[789]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[790]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[791]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[792]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[793]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[794]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[795]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[796]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[797]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[798]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[799]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[800]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[801]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[802]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[803]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[804]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[805]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[806]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[807]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[808]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[809]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[810]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[811]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[812]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[813]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[814]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[815]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[816]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[817]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[818]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[819]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[820]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[821]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[822]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[823]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[824]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[825]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[826]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[827]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[828]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[829]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[830]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[831]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[832]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[833]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[834]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[835]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[836]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[837]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[838]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[839]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[840]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[841]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[842]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[843]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[844]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[845]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[846]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[847]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[848]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[849]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[850]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[851]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[852]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[853]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[854]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[855]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[856]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[857]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[858]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[859]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[860]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[861]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[862]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[863]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[864]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[865]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[866]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[867]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[868]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[869]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[870]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[871]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[872]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[873]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[874]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[875]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[876]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[877]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[878]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[879]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[880]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[881]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[882]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[883]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[884]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[885]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[886]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[887]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[888]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[889]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[890]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[891]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[892]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[893]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[894]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[895]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[896]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[897]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[898]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[899]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[900]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[901]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[902]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[903]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[904]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[905]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[906]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[907]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[908]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[909]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[910]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[911]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[912]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[913]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[914]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[915]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[916]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[917]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[918]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[919]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[920]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[921]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[922]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[923]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[924]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[925]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[926]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[927]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[928]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[929]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[930]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[931]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[932]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[933]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[934]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[935]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[936]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[937]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[938]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[939]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[940]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[941]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[942]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[943]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[944]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[945]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[946]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[947]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[948]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[949]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[950]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[951]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[952]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[953]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[954]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[955]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[956]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[957]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[958]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[959]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[960]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[961]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[962]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[963]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[964]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[965]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[966]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[967]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[968]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[969]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[970]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[971]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[972]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[973]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[974]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[975]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[976]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[977]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[978]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[979]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[980]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[981]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[982]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[983]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[984]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[985]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[986]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[987]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[988]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[989]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[990]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[991]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[992]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[993]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[994]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[995]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[996]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[997]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[998]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[999]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1000]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1001]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1002]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1003]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1004]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1005]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1006]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1007]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1008]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1009]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1010]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1011]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1012]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1013]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1014]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1015]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1016]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1017]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1018]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1019]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1020]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1021]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1022]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1023]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1024]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1025]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1026]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1027]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1028]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1029]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1030]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1031]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1032]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1033]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1034]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1035]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1036]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1037]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1038]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1039]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1040]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1041]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1042]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1043]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1044]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1045]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1046]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1047]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1048]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1049]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1050]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1051]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1052]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1053]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1054]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1055]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1056]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1057]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1058]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1059]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1060]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1061]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1062]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1063]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1064]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1065]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1066]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1067]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1068]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1069]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1070]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1071]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1072]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1073]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1074]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1075]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1076]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1077]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1078]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1079]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1080]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1081]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1082]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1083]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1084]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1085]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1086]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1087]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1088]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1089]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1090]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1091]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1092]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1093]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1094]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1095]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1096]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1097]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1098]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1099]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1100]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1101]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1102]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1103]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1104]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1105]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1106]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1107]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1108]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1109]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1110]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1111]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1112]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1113]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1114]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1115]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1116]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1117]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1118]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1119]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1120]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1121]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1122]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1123]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1124]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1125]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1126]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1127]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1128]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1129]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1130]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1131]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1132]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1133]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1134]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1135]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1136]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1137]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1138]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1139]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1140]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1141]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1142]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1143]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1144]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1145]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1146]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1147]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1148]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1149]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1150]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1151]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1152]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1153]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1154]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1155]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1156]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1157]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1158]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1159]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1160]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1161]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1162]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1163]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1164]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1165]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1166]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1167]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1168]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1169]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1170]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1171]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1172]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1173]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1174]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1175]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1176]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1177]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1178]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1179]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1180]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1181]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1182]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1183]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1184]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1185]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1186]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1187]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1188]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1189]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1190]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1191]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1192]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1193]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1194]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1195]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1196]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1197]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1198]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1199]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1200]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1201]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1202]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1203]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1204]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1205]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1206]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1207]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1208]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1209]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1210]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1211]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1212]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1213]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1214]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1215]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1216]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1217]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1218]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1219]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1220]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1221]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1222]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1223]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1224]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1225]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1226]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1227]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1228]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1229]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1230]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1231]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1232]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1233]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1234]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1235]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1236]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1237]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1238]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1239]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1240]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1241]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1242]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1243]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1244]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1245]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1246]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1247]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1248]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1249]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1250]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1251]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1252]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1253]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1254]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1255]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1256]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1257]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1258]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1259]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1260]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1261]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1262]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1263]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1264]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1265]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1266]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1267]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1268]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1269]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1270]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1271]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1272]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1273]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1274]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1275]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1276]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1277]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1278]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1279]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1280]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1281]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1282]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1283]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1284]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1285]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1286]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1287]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1288]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1289]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1290]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1291]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1292]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1293]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1294]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1295]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1296]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1297]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1298]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1299]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1300]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1301]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1302]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1303]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1304]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1305]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1306]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1307]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1308]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1309]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1310]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1311]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1312]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1313]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1314]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1315]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1316]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1317]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1318]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1319]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1320]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1321]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1322]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1323]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1324]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1325]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1326]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1327]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1328]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1329]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1330]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1331]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1332]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1333]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1334]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1335]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1336]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1337]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1338]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1339]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1340]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1341]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1342]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1343]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1344]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1345]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1346]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1347]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1348]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1349]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1350]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1351]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1352]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1353]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1354]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1355]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1356]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1357]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1358]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1359]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1360]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1361]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1362]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1363]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1364]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1365]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1366]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1367]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1368]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1369]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1370]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1371]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1372]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1373]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1374]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1375]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1376]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1377]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1378]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1379]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1380]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1381]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1382]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1383]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1384]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1385]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1386]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1387]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1388]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1389]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1390]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1391]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1392]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1393]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1394]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1395]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1396]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1397]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1398]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1399]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1400]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1401]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1402]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1403]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1404]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1405]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1406]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1407]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1408]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1409]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1410]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1411]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1412]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1413]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1414]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1415]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1416]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1417]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1418]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1419]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1420]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1421]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1422]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1423]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1424]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1425]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1426]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1427]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1428]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1429]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1430]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1431]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1432]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1433]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1434]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1435]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1436]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1437]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1438]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1439]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1440]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1441]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1442]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1443]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1444]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1445]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1446]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1447]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1448]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1449]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1450]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1451]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1452]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1453]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1454]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1455]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1456]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1457]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1458]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1459]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1460]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1461]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1462]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1463]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1464]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1465]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1466]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1467]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1468]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1469]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1470]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1471]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1472]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1473]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1474]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1475]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1476]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1477]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1478]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1479]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1480]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1481]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1482]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1483]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1484]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1485]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1486]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1487]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1488]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1489]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1490]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1491]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1492]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1493]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1494]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1495]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1496]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1497]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1498]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1499]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1500]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1501]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1502]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1503]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1504]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1505]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1506]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1507]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1508]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1509]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1510]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1511]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1512]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1513]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1514]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1515]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1516]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1517]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1518]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1519]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1520]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1521]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1522]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1523]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1524]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1525]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1526]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1527]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1528]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1529]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1530]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1531]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1532]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1533]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1534]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1535]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1536]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1537]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1538]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1539]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1540]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1541]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1542]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1543]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1544]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1545]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1546]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1547]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1548]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1549]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1550]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1551]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1552]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1553]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1554]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1555]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1556]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1557]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1558]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1559]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1560]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1561]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1562]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1563]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1564]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1565]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1566]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1567]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1568]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1569]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1570]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1571]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1572]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1573]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1574]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1575]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1576]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1577]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1578]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1579]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1580]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1581]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1582]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1583]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1584]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1585]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1586]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1587]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1588]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1589]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1590]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1591]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1592]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1593]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1594]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1595]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1596]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1597]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1598]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1599]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1600]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1601]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1602]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1603]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1604]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1605]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1606]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1607]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1608]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1609]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1610]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1611]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1612]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1613]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1614]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1615]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1616]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1617]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1618]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1619]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
#>
#> [[1620]]
#> # A tibble: 1,620 × 13
#> lda_model booster eta max_depth gamma subsample colsample_bylevel nrounds
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 k_5 gbtree 0.01 3 0 0.5 0.5 5
#> 2 k_5 gbtree 0.01 3 0 0.5 0.5 30
#> 3 k_5 gbtree 0.01 3 0 0.5 0.5 55
#> 4 k_5 gbtree 0.01 3 0 0.5 0.75 5
#> 5 k_5 gbtree 0.01 3 0 0.5 0.75 30
#> 6 k_5 gbtree 0.01 3 0 0.5 0.75 55
#> 7 k_5 gbtree 0.01 3 0 0.5 1 5
#> 8 k_5 gbtree 0.01 3 0 0.5 1 30
#> 9 k_5 gbtree 0.01 3 0 0.5 1 55
#> 10 k_5 gbtree 0.01 3 0 0.75 0.5 5
#> # ℹ 1,610 more rows
#> # ℹ 5 more variables: objective <chr>, num_parallel_tree <dbl>,
#> # xgb_model <list>, error <dbl>, importance <dt[,1]>
